import pandas as pd
coins_data = pd.read_csv("C://college//data visualization//final pap//Cryptocurrency-Visualization-main////Dataset/top_coins.csv")
coins_data
| Date | Open | High | Low | Close | Adj Close | Volume | Currency | |
|---|---|---|---|---|---|---|---|---|
| 0 | 10/1/2015 | 236.004 | 238.445 | 235.616 | 237.549 | 237.549 | 20488800 | Bitcoin |
| 1 | 10/2/2015 | 237.264 | 238.541 | 236.603 | 237.293 | 237.293 | 19677900 | Bitcoin |
| 2 | 10/3/2015 | 237.202 | 239.315 | 236.944 | 238.730 | 238.730 | 16482700 | Bitcoin |
| 3 | 10/4/2015 | 238.531 | 238.968 | 237.940 | 238.259 | 238.259 | 12999000 | Bitcoin |
| 4 | 10/5/2015 | 238.147 | 240.383 | 237.035 | 240.383 | 240.383 | 23335900 | Bitcoin |
| ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 35733 | 9/26/2020 | 68.514 | 69.631 | 68.514 | 69.184 | 69.184 | 298621240 | Dash |
| 35734 | 9/27/2020 | 69.183 | 69.885 | 67.430 | 68.749 | 68.749 | 284471075 | Dash |
| 35735 | 9/28/2020 | 68.749 | 70.044 | 67.517 | 67.521 | 67.521 | 296838687 | Dash |
| 35736 | 9/29/2020 | 67.511 | 68.794 | 67.040 | 68.659 | 68.659 | 286638250 | Dash |
| 35737 | 9/30/2020 | 68.596 | 69.109 | 66.886 | 69.109 | 69.109 | 266434156 | Dash |
35738 rows × 8 columns
from pandas_visual_analysis import VisualAnalysis
VisualAnalysis(coins_data)
import matplotlib.pyplot as plt
import pandas as pd
import seaborn as sns
import numpy as np
import scipy.stats as ss
sns.set_style('white')
sns.pairplot(coins_data, hue='Currency')
coins_data.plot()
bitcoin_data = pd.read_csv("C://college//data visualization//final pap//Cryptocurrency-Visualization-main////Dataset/bitcoin_data.csv")
bitcoin_data
| Date | Open | High | Low | Close | Adj Close | Volume | |
|---|---|---|---|---|---|---|---|
| 0 | 2014-09-17 | 465.864014 | 468.174011 | 452.421997 | 457.334015 | 457.334015 | 2.105680e+07 |
| 1 | 2014-09-18 | 456.859985 | 456.859985 | 413.104004 | 424.440002 | 424.440002 | 3.448320e+07 |
| 2 | 2014-09-19 | 424.102997 | 427.834991 | 384.532013 | 394.795990 | 394.795990 | 3.791970e+07 |
| 3 | 2014-09-20 | 394.673004 | 423.295990 | 389.882996 | 408.903992 | 408.903992 | 3.686360e+07 |
| 4 | 2014-09-21 | 408.084991 | 412.425995 | 393.181000 | 398.821014 | 398.821014 | 2.658010e+07 |
| ... | ... | ... | ... | ... | ... | ... | ... |
| 2201 | 2020-09-26 | 10702.237305 | 10778.500000 | 10682.082031 | 10754.437500 | 10754.437500 | 1.810501e+10 |
| 2202 | 2020-09-27 | 10752.939453 | 10804.732422 | 10643.458008 | 10774.426758 | 10774.426758 | 1.801688e+10 |
| 2203 | 2020-09-28 | 10771.641602 | 10949.123047 | 10716.676758 | 10721.327148 | 10721.327148 | 2.272037e+10 |
| 2204 | 2020-09-29 | 10712.462891 | 10858.939453 | 10665.344727 | 10848.830078 | 10848.830078 | 2.045987e+10 |
| 2205 | 2020-09-30 | 10845.411133 | 10856.528320 | 10689.670898 | 10787.618164 | 10787.618164 | 2.075962e+10 |
2206 rows × 7 columns
plt.xlabel("Open")
plt.ylabel("Close")
plt.scatter(bitcoin_data["Close"], bitcoin_data["Volume"])
<matplotlib.collections.PathCollection at 0x1a69c1aac08>
coin_data_500 = coins_data[:5000]
coin_data_500['High']
0 238.445
1 238.541
2 239.315
3 238.968
4 240.383
...
4995 104.844
4996 111.334
4997 120.640
4998 119.498
4999 119.133
Name: High, Length: 5000, dtype: float64
import altair as alt
from altair.expr import datum, substring
alt.Chart(coins_data[:5000]).mark_point().encode(
x='Low',
y='High',
color='Currency:N'
).properties(
width=650,
height=400
).project(
type='albersUsa'
)
import plotly.express as px
fig = px.scatter(coins_data, x="Open", y="Date", color="Currency")
fig.show()
fig = px.histogram(coins_data,x="Date", y="Volume", color="Currency", marginal="box",
height=400)
fig.show()
def make_example(selector):
return alt.Chart(coins_data[:5000]).mark_rect().encode(
x="High", y="Low", color="Currency"
).properties(
width=600,
height=400
).add_selection(
selector
)
interval = alt.selection_interval()
make_example(interval)
df_bitcoin = pd.read_csv("C://college//data visualization//final pap//Cryptocurrency-Visualization-main////Dataset/bitcoin_data.csv")
px.line(df_bitcoin, x= "Date", y = "Close")
px.area(df_bitcoin, x = "Date", y = "Volume")
import plotly.graph_objs as go
fig = go.Figure(data = [go.Candlestick(x = df_bitcoin['Date'],
open = df_bitcoin['Open'],
high = df_bitcoin['High'],
low = df_bitcoin['Low'],
close = df_bitcoin['Close']
)])
fig.show()